However, all these graph neural networks have a common characteristic: focus on node rather than edge features. Only very few works have tried to integrate edge features into GNN architecture. Schlichtkrull et al.[1]} proposed an extension architecture of GCNs named R-GCNs. Gong et al.[2]} presented a framework that augments GCNs and GATs with edges. However, such approaches are somewhat not as reasonable as they are. We will highlight their limitations in the next section.
